The analysis of randomized response “ever” and “last year” questions: a non-saturated multinomial model
The analysis of randomized response “ever” and “last year” questions: a non-saturated multinomial model
Randomized response (RR) is a well-known interview technique designed to eliminate evasive response bias that arises from asking sensitive questions. The most frequently asked questions in RR are either whether respondents were “ever” carriers of the sensitive characteristic, or whether they were carriers in a recent period, for instance, “last year”. The present paper proposes a design in which both questions are asked, and derives a multinomial model for the joint analysis of these two questions. Compared to the separate analyses with the binomial model, the model makes a useful distinction between last year and former carriers of the sensitive characteristic, it is more efficient in estimating the prevalence of last year carriers, and it has a degree of freedom that allows for a goodness-of-fit test. Furthermore, it is easily extended to a multinomial logistic regression model to investigate the effects of covariates on the prevalence estimates. These benefits are illustrated in two studies on the use of anabolic androgenic steroids in the Netherlands, one using Kuk and one using both the Kuk and forced response. A salient result of our analyses is that the multinomial model provided ample evidence of response biases in the forced response condition.
Anabolic steroids, Efficiency, Forced response, Goodness-of-fit, Kuk model, Multinomial logistic, Randomized response, Response bias
Sayed, Khadiga H.A.
9f0ba98e-f5a6-41c1-8e29-9ef779803ff9
Cruyff, Maarten J. L. F.
98cda6ff-1ec3-4dc3-9d6e-eb0c7c538e70
Van Der Heijden, Peter
85157917-3b33-4683-81be-713f987fd612
10 May 2023
Sayed, Khadiga H.A.
9f0ba98e-f5a6-41c1-8e29-9ef779803ff9
Cruyff, Maarten J. L. F.
98cda6ff-1ec3-4dc3-9d6e-eb0c7c538e70
Van Der Heijden, Peter
85157917-3b33-4683-81be-713f987fd612
Sayed, Khadiga H.A., Cruyff, Maarten J. L. F. and Van Der Heijden, Peter
(2023)
The analysis of randomized response “ever” and “last year” questions: a non-saturated multinomial model.
Behavior Research Methods.
(doi:10.3758/s13428-023-02096-3).
Abstract
Randomized response (RR) is a well-known interview technique designed to eliminate evasive response bias that arises from asking sensitive questions. The most frequently asked questions in RR are either whether respondents were “ever” carriers of the sensitive characteristic, or whether they were carriers in a recent period, for instance, “last year”. The present paper proposes a design in which both questions are asked, and derives a multinomial model for the joint analysis of these two questions. Compared to the separate analyses with the binomial model, the model makes a useful distinction between last year and former carriers of the sensitive characteristic, it is more efficient in estimating the prevalence of last year carriers, and it has a degree of freedom that allows for a goodness-of-fit test. Furthermore, it is easily extended to a multinomial logistic regression model to investigate the effects of covariates on the prevalence estimates. These benefits are illustrated in two studies on the use of anabolic androgenic steroids in the Netherlands, one using Kuk and one using both the Kuk and forced response. A salient result of our analyses is that the multinomial model provided ample evidence of response biases in the forced response condition.
Text
Sayed Cruyff van der Heijden (2023) MBR Ever and last year
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More information
Accepted/In Press date: 15 February 2023
e-pub ahead of print date: 10 May 2023
Published date: 10 May 2023
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Publisher Copyright:
© 2023, The Author(s).
Keywords:
Anabolic steroids, Efficiency, Forced response, Goodness-of-fit, Kuk model, Multinomial logistic, Randomized response, Response bias
Identifiers
Local EPrints ID: 476920
URI: http://eprints.soton.ac.uk/id/eprint/476920
ISSN: 1554-351X
PURE UUID: e48d4219-f36f-478e-9c0c-4e8d407d0a74
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Date deposited: 19 May 2023 16:37
Last modified: 06 Jun 2024 01:51
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Author:
Khadiga H.A. Sayed
Author:
Maarten J. L. F. Cruyff
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